Akwa GGZ – Mental health analytics

Healthcare

GGZ Data Portal offers mental health professionals, organizations, and networks a free and secure platform to gain more insight into treatments for continuous quality improvement.

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Industry

Healthcare

Location

Netherlands

Project duration

icon 5 Months

Services

Backend Development

Shortly
about the
app

GGZ Data Portal offers mental health professionals, organizations, and networks a free and secure platform to gain more insight into treatments for continuous quality improvement.

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GGZ Data Portal offers mental health professionals, organizations, and networks a free and secure platform to gain more insight into treatments for continuous quality improvement.

Main Features

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Main Goal

To create a scalable microservice application that will extract data from health care providers and perform multiple data manipulations that allow doctors and care providers to take action based on the aggregated data.

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Components connection

All the developed system components are combined together with the power of docker and its great networking. All microservices are always kept in touch and can easily communicate with each other via an HTTP protocol in the private docker network.

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Faster than Fast

To meet business needs and to speed up the development process - the great tool was chosen - FastAPI. It's great for building microservices and it has shown its greatest advantages during development and production.

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Inspecting the data

For each specific healthcare data - there's an admin panel that aggregates, displays, and allows users to interact with the data - with that opportunity healthcare providers can better understand the mental health of their patients and make a treatment more efficient

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Fully automated and fully concurrent

Every microservice is fully sustainable and concurrent by itself - it means that even if every healthcare provider in the country will use the system - there'll always be available services and resources to manage and process the given request.

Technologies
we used

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Python

Docker

FastAPI

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